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All Journal Jurnal Health Sains Media Publikasi Promosi Kesehatan Indonesia (MPPKI)
Handari, Rahma Dewi
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Dentistry Health Professions Medicine & Pharmacology Nursing Public Health Veterinary

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Prevalensi dan Faktor Risiko Kejadian Efek Samping Obat pada Pasien TB-MDR: Literature Review: Prevalence and Risk Factors for Adverse Drug Reactions in MDR-TB Patients: Literature Review Handari, Rahma Dewi; Ronoatmodjo , Sudarto
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 7 No. 3: MARCH 2024 - Media Publikasi Promosi Kesehatan Indonesia (MPPKI)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v7i3.4700

Abstract

Latar belakang: Efek samping obat merupakan masalah kesehatan penting yang sering terjadi pada pengobatan Tuberculosis Multi Drug Resistant (TB-MDR) dan berpengaruh pada kepatuhan pengobatan dan keberhasilan pengobatan. Tujuan: Untuk mengetahui gambaran efek samping dan faktor risiko yang berhubungan dengan terjadinya efek samping obat pada pasien TB-MDR. Metode: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Penelusuran literatur pada database Pubmed, Proquest, Scopus dan Science Direct. Kata kunci: “adverse event” “adverse drug reaction” “drug resistant” “MDR” “tuberculosis” “predicted factor”. Kriteria inklusi literatur berbahasa Inggris, full text, free open access, rentang waktu publikasi 10 tahun terakhir, dan memiliki desain studi analitik. Hasil: Berdasarkan hasil penelusuran di 4 database diperoleh total 468 artikel yang kemudian dilakukan proses skrining dan kelayakan melalui kriteria inklusi dan eksklusi hingga didapatkan 6 artikel yang dilakukan sintesis. Kesimpulan: Prevalensi efek samping pasien TB-MDR adalah 40-80,7%. Mayoritas pasien mengalami efek samping ototoxicity, arthralgia, gastrointestinal disease, psychiatric disturbance, hepatotoxicity, dermatologic disease. Faktor risiko yang berhubungan dengan efek samping adalah usia lebih tua, berat badan tinggi, status pasien yang bekerja, riwayat efek samping, riwayat pengobatan TB sensitive obat (SO), komorbiditas, alkohol, dan perokok aktif, paduan pengobatan TB-MDR (paduan jangka panjang, paduan individual, paduan tanpa bedaquiline), tidak menerima transportasi kontrol bulanan, menerima DOT (directly observed therapy) dari fasilitas kesehatan perifer, dan keterlambatan pelaporan kasus TB MDR. Sedangkan faktor yang menurunkan risiko efek samping adalah paduan pengobatan dengan bedaquiline, underweight dan menerima pasokan makanan
Surrogate Biomarker to Identify Obesity and Predict Cardiovascular Disease Risk: A Systematic Review Azzumar, Farchan; Helda, Helda; Salamah, Qonita Nur; Handari, Rahma Dewi; Ramadhani, Ramadhani; Ibna, Reihana Ramadlani; Herawati, Yanti
Jurnal Health Sains Vol. 5 No. 7 (2024): Journal Health Sains
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jhs.v5i7.1302

Abstract

The study investigates the relationship between obesity and cardiovascular disease (CVD) risk, comparing the use of body mass index (BMI) versus other biomarkers in predicting CVD risk among obese individuals. It conducts a systematic literature review following the PRISMA guidelines, searching databases for relevant articles published from 2017-2022. The review analyzes 12 eligible articles and finds that factors beyond just BMI, such as genetics, physical activity, metabolic disorders, previous heart disease history, nutrition, fat distribution, and changes in BMI, can significantly impact the prognosis of heart disease in obese individuals. Importantly, the study shows that measures of fat distribution, like waist-to-height ratio, waist circumference, log-transformed body shape index (LBSIZ), and the ratio of visceral adipose tissue (VAT) to subcutaneous adipose tissue (SAT), are superior to BMI in predicting CVD risk among those with obesity. The key takeaway is that while obesity is strongly linked to CVD risk, BMI alone often fails to predict that risk accurately. Fat distribution measures may be a more effective tool for identifying obesity status and predicting associated CVD risk compared to relying solely on BMI.
Co-Authors Azzumar, Farchan Helda Helda Herawati, Yanti Ibna, Reihana Ramadlani Ramadhani Ramadhani Ronoatmodjo , Sudarto Salamah, Qonita Nur